This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. We propose to develop and demonstrate TeraGrid enabled national scale agent-based simulations of the spread of infectious disease. In particular, we are interested in understanding the limitations of large Symmstric Multiprocessing (SMP) shared memory machines for these types of simulations. This work is part of the NIGMS sponsored MIDAS program that has been tasked with developing national scale modeling tools for pandemic preparedness. And important issue in these types of models is their scalability in terms of large populations. Previous work using the Imperial Model reported by Ferguson et. al. has shown that large scale simulations are possible. However, the general unavailability of large SMP machines has limited the time to complete an experiment involving many hundreds of runs. We foresee that the computational resources located at the Pittsburgh Supercomputing Center would allow us to accelerate the production of experimental results using simulated populations representative of the population of the United States. This study therefore offers the opportunity to explore both the usefulness of large scale simulations and the appropriateness of TeraGrid resources for models of this size.